#!/bin/bash
# 
# Developed by Fred Weinhaus 9/16/2007 .......... revised 11/25/2012
# 
# USAGE: statsfilt [-s statistic] [-p power] infile outfile
# USAGE: statsfilt [-h or -help]
# 
# OPTIONS:
# 
# -s        statistic      id number for the statistical filter to compute; default=1
#                          statistic=1:  simple average (arithmetic mean) of neighborhood 
#                                        pixels
#                          statistic=2:  minimum value of neighborhood pixels
#                          statistic=3:  maximum value of neighborhood pixels
#                          statistic=4:  average of the minimum and maximum values
#                          statistic=5:  arithmetic mean without the min and max
#                          statistic=6:  standard deviation of the neighborhood pixels
#                          statistic=7:  geometric mean of the neighborhood pixels
#                          statistic=8:  harmonic mean of the neighborhood pixels
#                          statistic=9:  Lp mean of the neighborhood pixels;
#                                        require p=integer option
#                          statistic=10: contraharmonic mean of the neighborhood pixels;
#                                        require p=integer option
#                          statistic=11: linear distance weighted average of neighborhood
#                                        pixels, excluding the center
#                          statistic=12: inverse distance weighted average of neighborhood
#                                        pixels, excluding the center
#                          statistic=13: minimum or maximum whichever value is closest 
#                                        to center 
#                          statistic=14: average (arithmetic mean) without the center pixel 
# -p         power         exponent value to use with statistic 9 and 10; 
#                          exponent=integer; default=2
# -h         get help
# -help      get help
# 
###
# 
# NAME: STATSFILT 
# 
# PURPOSE: To compute various localized (neighborhood) statistical filters on an image. 
# 
# DESCRIPTION: STATSFILT is a collection of localized (neighborhood) statistical 
# filters most of which are used for noise reduction in an image. Note that most 
# noise reduction filters trade noise reduction for some degree of blurring.
# 
# Arguments: 
# 
# -h or -help    ---  displays help information. 
# 
# -s     statistic   statistic is a numerical id for the type of
# statistic to be calculated. 
# 
# A value of 1 replaces each input pixel with the simple average 
# (or arithmetic mean) of all the pixels in the 3x3 neighborhood about 
# that input pixel.
# 
# A value of 2 replaces the input pixel with the minimum value found in
# the neighborhood.
# 
# A value of 3 replaces the input pixel with the maximum value found in
# the neighborhood.
# 
# A value of 4 replace the input pixel with average of the minimum and
# maximum values in the neighborhood.
# 
# A value of 5 replaces the input pixel with simple average of all the
# pixels in the neighborhood, except the minimum and maximum values. 
# Thus it is throwing out the two extreme outliers.
# 
# A value of 6 replaces the input pixel with the standard deviation of
# all the pixels in the neighborhood. This is more of an edge operator
# that a noise reduction operator.
# 
# A value of 7 replaces the input pixel with geometric mean of all the
# pixels in the neighborhood. The geometric mean is computed by taking
# the ln of each neigborhood pixel value, averaging these values and
# then taking the exp of the result. The geometric mean is used 
# especially for noise reduction when dealing with one-sided noise 
# that is all bright spikes (but not well at all dark spikes).
# 
# A value of 8 replaces the input pixel with the harmonic mean of all
# the pixels in the neighborhood. The harmonic mean is computed by
# taking the inverse of each pixel value, averaging these results and
# then taking the inverse of the result. The harmonic mean is used 
# especially for noise reduction when dealing with one-sided noise 
# that is all bright spikes (but not well at all dark spikes).
# 
# A value of 9 replaces the input pixel with the Lp mean of all the
# pixels in the neighborhood. The Lp mean is computed by raising each
# pixel value in the neighborhood to some power, averaging these results
# and then raising the result to the equivalent inverse power (i.e. the
# negative value of the power). A choice of p=0 is not allowed.
# Typically p is a low valued integer, i.e. 2 or -2. Note that p=1 is 
# equivalent to the simple average (arithmetic mean) and p=-1 is 
# equivalent to the harmonic mean. The Lp mean is used especially for 
# noise reduction when dealing with one-sided noise that is either all 
# bright spikes or all dark spikes. For all bright spikes, use negative 
# p values and for all dark spikes, use positive p values.
# 
# A value of 10 replaces the input pixel with the contraharmonic mean 
# of all the pixels in the neighborhood. The contraharmonic mean is
# computed by taking the average of all the pixels in the neighborhood
# raised to the power p+1 and dividing that by the average of all the
# pixels in the neighborhood raised to the power p. The power p can be
# any integer. A choice of p=-1 is not allowed. Note that p=0 is 
# equivalent to the simple average (arithmetic mean). The contraharmonic 
# mean is used especially for noise reduction when dealing with one-sided 
# noise that is either all bright spikes or all dark spikes. For all bright 
# spikes, use negative p values and for all dark spikes, use positive p 
# values.
# 
# A value of 11 replaces each pixel in the input image with a linear 
# distance weighted average of all pixels in the neighborhood, except the
# original center pixel. Weighting is measured as one minus the absolute 
# difference between the graylevel of each neighbor and the center pixel.
# Thus pixels with smaller differences (i.e. values closer to that of the 
# the center pixel) are weighted higher.
# 
# A value of 12 replaces each pixel in the input image with an inverse 
# distance weighted average of all pixels in the neighborhood, except the
# original center pixel. Weighting is measured as inverse of the absolute 
# difference between the graylevel of each neighbor and the center pixel.
# Thus pixels with smaller differences (i.e. values closer to that of the 
# the center pixel) are weighted higher.
# 
# A value of 13 replaces each pixel in the input image with either the 
# minimum or maximum value of all pixels in the neighborhood, whichever 
# is closest in value to the given (center) pixel. This produces a 
# sharpening effect on the image.
# 
# A value of 14 replaces each pixel in the input image with the average 
# of all the pixels in the neighborhood, but the center pixel.
#
# All of these statistical filters are computed within a 3x3
# neighborhood only. As it is, some of the latter statistics take a very
# long time to compute since this script is based upon the use of fx.
# 
# -p     power        exponent value to use to raise the pixel value to the 
#                     given power. 
# The values may be positive or negative integers. The default is 2
# 
# CAVEAT: No guarantee that this script will work on all platforms, 
# nor that trapping of inconsistent parameters is complete and 
# foolproof. Use At Your Own Risk. 
# 
######
#

# set default value for statistic, power
statistic=1
p=2

# set directory for temporary files
dir="."    # suggestions are dir="." or dir="/tmp"

# set up functions to report Usage and Usage with Description
PROGNAME=`type $0 | awk '{print $3}'`  # search for executable on path
PROGDIR=`dirname $PROGNAME`            # extract directory of program
PROGNAME=`basename $PROGNAME`          # base name of program
usage1() 
	{
	echo >&2 ""
	echo >&2 "$PROGNAME:" "$@"
	sed >&2 -n '/^###/q;  /^#/!q;  s/^#//;  s/^ //;  4,$p' "$PROGDIR/$PROGNAME"
	}
usage2() 
	{
	echo >&2 ""
	echo >&2 "$PROGNAME:" "$@"
	sed >&2 -n '/^######/q;  /^#/!q;  s/^#*//;  s/^ //;  4,$p' "$PROGDIR/$PROGNAME"
	}

# function to report error messages
errMsg()
	{
	echo ""
	echo $1
	echo ""
	usage1
	exit 1
	}

# function to test for minus at start of value of second part of option 1 or 2
checkMinus()
	{
	test=`echo "$1" | grep -c '^-.*$'`   # returns 1 if match; 0 otherwise
    [ $test -eq 1 ] && errMsg "$errorMsg"
	}

# test for correct number of arguments and get values
if [ $# -eq 0 ]
	then
	# help information
	echo ""
	usage2
	exit 0
elif [ $# -eq 3 -o $# -eq 5 -o $# -gt 6 ]
	then
	errMsg "--- TOO MANY ARGUMENTS WERE PROVIDED ---"
else
	while [ $# -gt 0 ]
		do
		# get parameters
		case "$1" in
	  -h|-help)    # help information
				   echo ""
				   usage2
				   ;;
			-s)    # statistic
				   shift  # to get the next parameter - statistic
				   # test if parameter starts with minus sign 
				   errorMsg="--- INVALID STATISTIC SPECIFICATION ---"
				   checkMinus "$1"
				   statistic=`expr "$1" : '\([0-9]*\)'`
				   [ "$statistic" = "" ] && errMsg "--- STATISTICS=$statistic MUST BE AN INTEGER ---"
				   statstestA=`echo "$statistic < 1" | bc`
				   statstestB=`echo "$statistic > 14" | bc`
				   [ $statstestA -eq 1 -o $statstestB -eq 1 ] && errMsg "--- STATISTICS=$statistic MUST BE AN INTEGER GREATER THAN 0 AND LESS THAN 14 ---"
				   ;;
			-p)    # power
				   shift  # to get the next parameter - power
				   p=`expr "$1" : '\([0-9-]*\)'`
				   [ "$p" = "" ] && errMsg "--- POWER=$p MUST BE AN INTEGER ---"
				   ;;
			 -)    # STDIN and end of arguments
				   break
				   ;;
			-*)    # any other - argument
				   errMsg "--- UNKNOWN OPTION ---"
				   ;;
			*)     # end of arguments
				   break
				   ;;
		esac
		shift   # next option
	done
	#
	# get infile and outfile
	infile=$1
	outfile=$2
fi

# test that infile provided
[ "$infile" = "" ] && errMsg "NO INPUT FILE SPECIFIED"
# test that outfile provided
[ "$outfile" = "" ] && errMsg "NO OUTPUT FILE SPECIFIED"

# setup temporary images and auto delete upon exit
# use mpc/cache to hold input image temporarily in memory
tmpA="$dir/statsfilt_$$.mpc"
tmpB="$dir/statsfilt_$$.cache"
tmp0="$dir/statsfilt_0_$$.png"
tmp1="$dir/statsfilt_1_$$.png"
tmp2="$dir/statsfilt_2_$$.png"
tmp3="$dir/statsfilt_3_$$.png"
tmp4="$dir/statsfilt_4_$$.png"
tmp5="$dir/statsfilt_5_$$.png"
tmp6="$dir/statsfilt_6_$$.png"
tmp7="$dir/statsfilt_7_$$.png"
tmp8="$dir/statsfilt_8_$$.png"
tmpw1="$dir/statsfilt_w1_$$.png"
tmpw2="$dir/statsfilt_w2_$$.png"
tmpw3="$dir/statsfilt_w3_$$.png"
tmpw4="$dir/statsfilt_w4_$$.png"
tmpw5="$dir/statsfilt_w5_$$.png"
tmpw6="$dir/statsfilt_w6_$$.png"
tmpw7="$dir/statsfilt_w7_$$.png"
tmpw8="$dir/statsfilt_w8_$$.png"
tmpMin="$dir/statsfilt_min_$$.png"
tmpMax="$dir/statsfilt_max_$$.png"
trap "rm -f $tmpA $tmpB $tmp0 $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 $tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 $tmpMin $tmpMax; exit 0" 0
trap "rm -f $tmpA $tmpB $tmp0 $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 $tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 $tmpMin $tmpMax; exit 1" 1 2 3 15

echo ""
echo "Please Wait - Filters 11 And 12 Take About 20 seconds To Process A 128x128 Image"
echo "Whereas - Filters 1-10, 13, 14 Take Only A Few Seconds To Process A 128x128 Image"
echo ""

# process data
ave="1,1,1,1,1,1,1,1,1"
pixels="aa=p[-1,-1]; ab=p[0,-1]; ac=p[+1,-1]; ba=p[-1,0]; bb=p[0,0]; bc=p[+1,0]; ca=p[-1,+1]; cb=p[0,+1]; cc=p[+1,+1];"
grav1="NorthWest"
grav2="North"
grav3="NorthEast"
grav4="East"
grav5="SouthEast"
grav6="South"
grav7="SouthWest"
grav8="West"
if convert -quiet -regard-warnings "$infile" +repage "$tmpA"
	then
	width=`identify -format %w $tmpA`
	height=`identify -format %h $tmpA`
	width2=`expr $width - 2`
	height2=`expr $height - 2`
	else
		errMsg "--- FILE $infile DOES NOT EXIST OR IS NOT AN ORDINARY FILE, NOT READABLE OR HAS ZERO SIZE ---"
fi

# function to create 8 1-pixel shifted images in each direction from center
shiftimages()
	{
	# create 8 shifted images
	image="$1"
	j=1
	while [ $j -lt 9 ]
		do
		eval grav=\$grav$j
		eval img=\$tmp$j
		convert $image $image[${width2}x${height2}+1+1] -gravity $grav -composite $img
		j=`expr $j + 1`
	done
	}

# get im version
im_version=`convert -list configure | \
	sed '/^LIB_VERSION_NUMBER /!d;  s//,/;  s/,/,0/g;  s/,0*\([0-9][0-9]\)/\1/g' | head -n 1`
	
# process images
case "$statistic" in
	1)	# arithmetic mean
		convert $tmpA -define convolve:scale=\! -convolve "$ave" $outfile
		;;
	2)	# min
		# create 8 shifted images
		shiftimages $tmpA

		# for each shifted image create successive min
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose darken -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $outfile
		;;
	3)	# max
		# create 8 shifted images
		shiftimages $tmpA

		# for each shifted image create successive max
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose lighten -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $outfile
		;;
	4)	# average of min and max		
		# create 8 shifted images
		shiftimages $tmpA

		# save input for dual use below
		convert $tmpA $tmp0
		
		# do min
		# for each shifted image create successive min
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose darken -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $tmpMin
		
		# initialize input again
		convert $tmp0 $tmpA
		
		# do max
		# recreate 8 shifted images from composite from first step above
		shiftimages $tmpA

		# for each shifted image create successive max
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose lighten -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $tmpMax
		
		# do average
		if [ "$im_version" -ge "06060904" ]; then 
			convert $tmpMin $tmpMax -evaluate-sequence mean $outfile
		else
			convert $tmpMin $tmpMax -average $outfile
		fi
		;;
	5)	# average without max an min
		# create 8 shifted images
		shiftimages $tmpA

		# save input for dual use below
		convert $tmpA $tmp0
		
		# do min
		# for each shifted image create successive min
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose darken -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $tmpMin
		
		# initialize input again
		convert $tmp0 $tmpA
		
		# do max
		# recreate shifted images from composite from step above
		shiftimages $tmpA

		# for each shifted image create successive max
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose lighten -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $tmpMax
		
		# do average
		# this does not work but should?
#		convert $tmp0 $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 -average $tmp0
#		convert $tmp0 $tmpMin $tmpMax -fx "((9*u[0])-u[1]-u[2])/7" $outfile
		# this works, but is slower
		if [ "$im_version" -lt "0608005" ]; then
			convert $tmp0 $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 $tmpMin $tmpMax -fx "(u[0]+u[1]+u[2]+u[3]+u[4]+u[5]+u[6]+u[7]+u[8]-u[9]-u[10])/7" $outfile
		else
			ff=`convert xc: -format "%[fx:1/7]" info:`
			convert $tmp0 $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 $tmpMin $tmpMax -evaluate multiply $ff -poly "1,1 1,1 1,1 1,1 1,1 1,1 1,1 1,1 1,1 -1,1 -1,1" $outfile
		fi		
		;;
	6)	# standard deviation
		# -gamma 2 is equivalent to sqrt
		convert $tmpA -define convolve:scale=\! -convolve "$ave" $tmp0
		convert \( $tmpA $tmpA -compose multiply -composite -define convolve:scale=\! -convolve "$ave" \) \
			\( $tmp0 $tmp0 -compose multiply -composite \) +swap \
			-compose minus -composite -gamma 2 $outfile
		;;
	7)	# geometric mean
		# fx range 0-1, but ln(1)=0 and ln(0)=-infinity, so add 1 to every value and normalize by ln(2) and remove 1 at end
		# convert $tmpA -fx "ln(u+1)/ln(2)" -define convolve:scale=\! -convolve $ave -fx "exp(u*ln(2))-1" $outfile
		# note don't need to normalize as ln(2)=.7 < 1; get same result as above
		convert $tmpA -fx "ln(u+1)" -define convolve:scale=\! -convolve $ave -fx "exp(u)-1" $outfile
		;;
	8)	# harmonic mean
		# fx range 0-1, but 1/x(1)=1 and 1/x(0)=infinity, so add 1 to every value and remove 1 at end
		convert $tmpA -fx "1/(u+1)" -define convolve:scale=\! -convolve $ave -fx "(1/u)-1" $outfile
		;;
	9)	# Lp mean
   		[ $p -eq 0 ] && errMsg "--- POWER CANNOT BE ZERO ---"
   		ptestA=`echo "scale=0; $p > -2" | bc`
   		ptestB=`echo "scale=0; $p < 2" | bc`
		[ $ptestA -eq 1 -a $ptestB -eq 1 ] && errMsg "--- POWER=$p MUST BE AN INTEGER LESS THAN -1 AND GREATER THAN 1 ---"
		ip=`echo "scale=10; 1 / $p" | bc`
		# to avoid problems with (positive noise and) p=neg i.e. 1/(0^p)=infinity; simply negate the image and use p=pos
		# note for p=-1, negating and using p=1 does not work as it is just the same as a plain average.
		if [ $p -lt 0 ]
			then
			p=`echo "scale=0; - $p / 1" | bc`
			ip=`echo "scale=10; 1 / $p" | bc`
			#convert $tmpA -negate -fx "pow(u,$p)" -define convolve:scale=\! -convolve $ave -fx "pow(u,$ip)" -negate $outfile
			# -gamma is same as pow, just invert exponent
			convert $tmpA -negate -gamma $ip -define convolve:scale=\! -convolve $ave -gamma $p -negate $outfile
		else
			#convert $tmpA -fx "pow(u,$p)" -define convolve:scale=\! -convolve $ave -fx "pow(u,$ip)" $outfile
			# -gamma is same as pow, just invert exponent
			convert $tmpA -gamma $ip -define convolve:scale=\! -convolve $ave -gamma $p $outfile
		fi
		;;
   10)	# contraharmonic mean
   		[ $p -eq -1 ] && errMsg "--- POWER CANNOT BE NEGATIVE ONE ---"
   		ptestA=`echo "scale=0; $p > -2" | bc`
   		ptestB=`echo "scale=0; $p < 1" | bc`
		[ $ptestA -eq 1 -a $ptestB -eq 1 ] && errMsg "--- POWER=$p MUST BE AN INTEGER LESS THAN -1 AND GREATER THAN 0 ---"
		p1=`echo "scale=0; $p + 1" | bc`
		# to avoid problems with (positive noise and) p=neg i.e. 1/(0^p)=infinity; simply negate the image and use p=pos
		# note that it is still possible to have u/v=0 if v=0; if this happens then use: 
		# incr=`echo "scale=10; 1 / 255" | bc` and
		# xx=(u-$incr)>=0?u:$incr; in fx
		if [ $p -lt 0 ]
			then
			p=`echo "scale=0; - $p" | bc`
			p1=`echo "scale=0; ($p + 1) / 1" | bc`
			#convert \( $tmpA -negate -fx "(pow((u),$p1))" -define convolve:scale=\! -convolve $ave \) \( $tmpA -negate -fx "(pow((u),$p))" -define convolve:scale=\! -convolve $ave \) -fx "(u/v)" -negate $outfile
			# -gamma is same as pow, just invert exponent
			pinv=`echo "scale=10; 1 / $p" | bc`
			p1inv=`echo "scale=10; 1 / $p1" | bc`
			convert \( $tmpA -negate -gamma $p1inv -define convolve:scale=\! -convolve $ave \) \( $tmpA -negate -gamma $pinv -define convolve:scale=\! -convolve $ave \) -fx "(u/v)" -negate $outfile

		else
			#convert \( $tmpA -fx "(pow((u),$p1))" -define convolve:scale=\! -convolve $ave \) \( $tmpA -fx "(pow((u),$p))" -define convolve:scale=\! -convolve $ave \) -fx "(u/v)" $outfile
			# -gamma is same as pow, just invert exponent
			pinv=`echo "scale=10; 1 / $p" | bc`
			p1inv=`echo "scale=10; 1 / $p1" | bc`
			convert \( $tmpA -gamma $p1inv -define convolve:scale=\! -convolve $ave \) \( $tmpA -gamma $pinv -define convolve:scale=\! -convolve $ave \) -fx "(u/v)" $outfile
		fi
		;;
   11)  # linear distance weighted average
		# weights are 1 minus grayscale absolute difference; if diff=0, then wt=1; if diff=1, then wt=0

		# create 8 shifted images
		shiftimages $tmpA

		: '
		# this does not work so well
		# create distance images
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			eval imgw=\$tmpw$j
			# get difference images then negate (equivalent to subtract from max) and change zero to 1 to avoid divide by zero
			convert $tmpA $img -compose difference -composite -negate -fill "rgb(1,1,1)" -opaque black $imgw
			# multiply shifted images by weights
			convert $img $imgw -compose multiply -composite $img
			j=`expr $j + 1`
		done
		# average the weighted images and the weights
		if [ "$im_version" -ge "06060904" ]; then 
			convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 -evaluate-sequence mean $tmpA
			convert $tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 -evaluate-sequence mean $tmp0
		else
			convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 -average $tmpA
			convert $tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 -average $tmp0
		fi
		# divide averages
		convert $tmpA $tmp0 -fx "u/v" $outfile
		'

		# this works fine but is slower than above
		# create distance images
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			eval imgw=\$tmpw$j
			# get difference images then negate (equivalent to subtract from max) and change zero to 1 to avoid divide by zero
			convert $tmpA $img -compose difference -composite -negate -fill "rgb(1,1,1)" -opaque black $imgw
			j=`expr $j + 1`
		done
		# create sum of weighted images and sum of weights then divide
		summ="((u[0]*u[8])+(u[1]*u[9])+(u[2]*u[10])+(u[3]*u[11])+(u[4]*u[12])+(u[5]*u[13])+(u[6]*u[14])+(u[7]*u[15]))"		
		wtSum="(u[8]+u[9]+u[10]+u[11]+u[12]+u[13]+u[14]+u[15])"
		convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 \
			$tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 \
			-fx "$wts u=($summ/$wtSum)" $outfile
		;;
   12)  # inverse distance weighted average		
		# create 8 shifted images
		shiftimages $tmpA
				
		: '
		# this does not work so well
		# create distance images
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			eval imgw=\$tmpw$j
			# get difference images and where value is zero change to max and then invert
			convert $tmpA $img -compose difference -composite -fill white -opaque black -fx "1/u" $imgw
			# multiply inverse weight images by shifted images to get weighted images
			convert $img $imgw -compose multiply -composite $img
			j=`expr $j + 1`
		done
		# average the weighted images
		if [ "$im_version" -ge "06060904" ]; then 
			convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 -evaluate-sequence mean $tmpA
		else
			convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 -average $tmpA
		fi
		# average the weight images
		if [ "$im_version" -ge "06060904" ]; then 
			convert $tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 -evaluate-sequence mean $tmp0
		else
			convert $tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 -average $tmp0
		fi
		# divide averages
		convert $tmpA $tmp0 -fx "u/v" $outfile
		'
		
		# this works fine but is slower than above
		# create distance images
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			eval imgw=\$tmpw$j
			# get difference images and where value is zero change to max
			convert $tmpA $img -compose difference -composite -fill white -opaque black $imgw
			j=`expr $j + 1`
		done
		# note this is faster than separating out the individual inverse wts and multiplying
		# create sum of inverse weighted images and sum of inverse weights then divide
		summ="((u[0]/u[8])+(u[1]/u[9])+(u[2]/u[10])+(u[3]/u[11])+(u[4]/u[12])+(u[5]/u[13])+(u[6]/u[14])+(u[7]/u[15]))"		
		wtSum="((1/u[8])+(1/u[9])+(1/u[10])+(1/u[11])+(1/u[12])+(1/u[13])+(1/u[14])+(1/u[15]))"
		convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 \
			$tmpw1 $tmpw2 $tmpw3 $tmpw4 $tmpw5 $tmpw6 $tmpw7 $tmpw8 \
			-fx "$wts u=($summ/$wtSum)" $outfile
		;;
   13)	# sharp filter: min or max, whichever is closest to center
		# create 8 shifted images
		shiftimages $tmpA

		# save input for dual use below
		convert $tmpA $tmp0
		
		# do min
		# for each shifted image create successive min
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose darken -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $tmpMin
		
		# initialize input again
		convert $tmp0 $tmpA
		
		# do max
		# recreate shifted images from composite from step above
		shiftimages $tmpA

		# for each shifted image create successive max
		j=1
		while [ $j -lt 9 ]
			do
			eval img=\$tmp$j
			convert $tmpA $img -compose lighten -composite $tmpA
			j=`expr $j + 1`
		done
		convert $tmpA $tmpMax
		
		# get result
		convert $tmp0 $tmpMin $tmpMax -fx "(abs(u[1]-u[0])<abs(u[2]-u[0]))?u[1]:u[2]" $outfile
		;;
   14)	# average without center pixel
		# create 8 shifted images
		shiftimages $tmpA

		# average 8 shifted images
		if [ "$im_version" -ge "06060904" ]; then 
			convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 -evaluate-sequence mean $outfile
		else
			convert $tmp1 $tmp2 $tmp3 $tmp4 $tmp5 $tmp6 $tmp7 $tmp8 -average $outfile
		fi
		;;
	*)  # no other options allowed
		errMsg "--- UNKNOWN STATISTICS ---"
		;;
esac
exit 0
